The present invention relates generally to systems that document the geometry and other attributes of objects in three dimensions and, specifically, to a system that employs a scanning lidar (range finding laser) to quickly and accurately sense the position in three-dimensional space of selected points on the surface of an object to generate a point cloud model which represents the sensed positions of the selected points. The point cloud model may be transformed into a further model usable by computer-aided design (CAD) tools, including conventional CAD tools.
Mapping the geometry (shape, dimensions and location) and other attributes (e.g., color, texture and reflectance intensity) of complex real objects (whether small components such as small mechanical parts or large objects such as buildings and sites) has conventionally been a tedious and time-consuming process that has been performed manually. In addition, transforming these measurements into drawings or computer models required manual drafting or input into a CAD system for the production of the drawing or computer models.
In the building industry, conventional methods of mapping a structure requires three basic steps: field data gathering, data reduction and preparation and drafting and CAD. The gathering step is performed by a team of surveyors who manually measure and record dimensions of pertinent components of the structure such as walls, ceilings, beams, columns, doors, windows, fixtures, pipes, conduits and equipment. The surveyors attempt to determine the geometry of the components as well as the relative location of the components in the structure and record the geometry and relative location in a field notebook. That information is then organized and reduced to tables and organized sketches. A CAD operator or drafter uses these tables to generate final drawings or models.
This process is labor intensive, time consuming, and error prone. In addition, using traditional surveying methods, the number of points which can actually be measured is very limited, due to the high cost of acquiring each point in terms of time and effort. Furthermore, if it is desired to acquire color, texture and other attribute information, additional field notes must be taken (e.g., still photographs and video).